Title: Using Big Data and Machine Learning to Uncover How Players Choose Mixed Strategies
Abstract: How do humans behave in a situation where (i) one needs to make one’s own behavior unpredictable and (ii) one needs to predict an opponent’s behavior? This is an important class of strategic situations, formulated as games with a mixed strategy equilibrium. If humans are put in such a situation, it is obvious that, rather than calculating the mixed equilibrium strategy, they use their hunches and some heuristics to achieve the aforementioned goals (i) and (ii). Exactly what kind of mechanisms are employed has not been fully understood. To address this issue, we use our unique big experimental data set about a game with a mixed strategy equilibrium, which has about 75,000 observations, and compare conventional behavioral economics models with some leading machine learning models. The use of big data enables us to examine the external validities of those models, i.e., compare the predictive powers of those models in data sets that are not used for parameter estimation. We found that machine learning models, most notably a version of the deep learning model LSTM, substantially outperform the leading behavioral model (EWA), and this happens only when the size of the data set for parameter estimation is sufficiently large. Finally, we try to improve the EWA model by incorporating the insights gained from the machine learning models.
Title: Robust Mechanisms for the Financing of Public Goods
Abstract: We propose a novel proportional cost-sharing mechanism for funding public goods with interdependent values. In this mechanism, the agents simultaneously submit “bids,” the expenditure on the public good is an increasing function of the sum of the bids, and each agent is responsible for the fraction of the expenditure proportional to their bid. The proportional cost-sharing mechanism provides a non-trivial guarantee for social welfare, regardless of the structure of the agents’ information and the equilibrium that is played, as long as the social value for the public good is sufficiently large. Moreover, this guarantee is shown to be unimprovable in environments where the designer knows a lower bound on the social value. These mechanisms guarantee the entire efficient surplus when the social value becomes large. When there are two agents, our model can be reinterpreted as one of bilateral trade.